混合神经网络在入侵检测中的应用研究

【作者】 刘军利；

【导师】 陈莉；

【作者基本信息】 西北大学 ， 计算机软件与理论， 2005， 硕士

【摘要】 随着计算机网络的发展和普及,网络入侵的手法日益复杂化和隐蔽化,传统的入侵检测方法的缺陷越来越明显。为了提高入侵检测系统检测的准确性以及检测效率,一些研究者将目光投向了神经网络。本文概述了神经网络在入侵检测中的研究现状,分析了BP和ART-2两种神经网络应用于网络入侵检测时各自的优缺点,并提出了相应的解决方案。最后,设计并实现了一个基于混合神经网络的网络入侵检测原型系统BA-NIDS,通过实验证明了混合神经网络应用于网络入侵检测系统的可行性和有效性。 本文的主要工作有: 1.分析了神经网络应用于入侵检测系统的国内外的研究现状,指出了BP网络应用于入侵检测系统的不足。提出了针对不同的攻击类型构造不同的BP网络的思想,通过仿真实验证明了这种方法的有效性。 2.分析了ART-2网络应用于网络入侵检测面临的问题,提出了一种具有更严格测试准则的ART-2网络,通过仿真实验证明了这种具有更严格测试准则的ART-2网络应用入侵检测系统的有效性。 3.分析了BP网络和ART-2网络应用于入侵检测系统各自的优缺点。提出了一种由若干个BP网络和一个ART-2网络组成的混合神经网络入侵检测模型,其中BP网络用来检测特定类型的入侵,ART-2网络用来检测:未知的攻击类型。 4.设计并实现了一个基于混合神经网络的网络入侵检测系统BA-NIDS,分析了设计系统时需要考虑的一些问题及系统实现的一些关键技术。仿真实验说明了将混合神经网络作为检测引擎,更具有可行性和应用性。更多还原

【Abstract】 With the development of network, the hijack intrudes our host more complicated and covertly. As a result, the traditional technology is discouraged to detect these intrusions. In order to improve the performance of intrusion detection system (IDS), some researchers pay their attention to neural network. In this paper, the achievement of applying neural network in IDS is summarized, the advantages and drawbacks of applying BP and ART-2 in IDS are pointed out, and the solutions to the problem are given out. In the last chapter, a novel IDS named BA-NIDS is implemented based on hybrid neural network. The validity of using hybrid neural network in IDS is certified by experiment.Main contributions of this dissertation are listed as following:Firstly, a review of IDS is presented, and the advantage and drawback of using BP in intrusion detection system are indicated. A novel method which is building different BP based on the different intrusion type is proposed, and experiments are used to validate this model’s performanc.Secondly, with the aim of making up the drawback of normal ART-2 suffered, a novel ART-2 neural network model with more vigorous vigilance test criterion is proposed. Then simulation experiments which are based on the KDDCUP 99 data set are used to validat the validation of applying this novel ART-2 on intrusion detection.Thirdly, BP is compared with ART-2 when used in intrusion detection and a novel IDS model which is blending the BP and ART-2 in IDS is put forward. BP is applied to detect specifically intrusion while ART-2 was used to detect unknown intrusion.Finally, a new IDS named BA-NIDS is implemented based on hybrid neural network, and the characters and functions of different components are introduced. The experiment results show that the BA-NIDS is validity and using the hybrid neural network in IDS is feasible.更多还原